We don't iterate on code. We iterate on concepts. Each version is a complete rebuild incorporating real learnings. No technical debt. No compromises.
• Build an MVP to minimize risk
• Iterate by adding features incrementally
• Accumulate technical debt with each addition
• Compromise architecture to ship faster
• Eventually need a complete rewrite
• Plan the complete product upfront
• Build it in days, test with real users
• Learn what's wrong, update the spec
• Rebuild from scratch with learnings
• Launch with clean, coherent architecture
The fundamental shift: Building isn't expensive anymore. AI can generate complete systems from specifications in days. So instead of building once and iterating on code, we iterate on the concept and rebuild. The code is disposable. The specification is what matters.
We don't just gather requirements. We architect the complete system. Every edge case. Every user flow. Every data structure. This takes time - but it's where the value is created.
Time investment: 30-40% of total project time. This is not wasted - this is where we prevent problems instead of fixing them later.
Generate the complete system from the specification. This takes days, not months. We're not writing code line-by-line - we're generating entire systems.
Time investment: 15-25% of project time. Fast because the specification is complete and precise.
Put it in front of real users. Not a prototype - a working product. Get real feedback. Learn what's actually needed vs what we thought was needed.
Time investment: 10-15% of project time. Real usage reveals truths that no amount of planning can predict.
Incorporate learnings into the specification. This isn't "fixing bugs" - it's fundamentally rethinking the approach based on real usage data.
Time investment: 10-15% of project time. The specification is the source of truth - this is where we encode our learnings.
Generate the complete system again from the updated specification. Clean architecture. No technical debt. No compromises. This is the version you launch.
Time investment: 20-30% of project time. Faster than v0.1 because we know exactly what we're building.
Each version starts from a clean slate. No accumulated compromises. No architectural decisions you regret. When you launch, you launch with production-quality code.
Building twice is faster than building once and then spending months fixing it. We can do 3 complete iterations in the time traditional development does one feature.
Real user feedback on complete implementations leads to better decisions. You're not guessing what users want - you're watching them use it.
Generating code is cheap. Thinking is expensive. We invest in clarity and architecture, not in typing. The result: better products for less money.
This isn't something you can just do by prompting ChatGPT. Making this work at production quality required deep expertise and significant investment.
Financial investment in tools, infrastructure, and experimentation
Full-time focus on figuring out how to make this work reliably
I didn't just learn to use AI tools. I systematically figured out:
This barrier to entry is why this approach works. Most people trying this casually will fail.
Book 30 minutes. I'll explain how this process would work for your specific project.
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